The present disclosure relates generally to fault accommodation in complex engineered systems using predictive modeling and optimization.
Fault accommodation is becoming an increasingly important subject for complex, fault-tolerant engineered systems, and in particular aircraft engine systems. Faults, if not suitably responded to in a timely manner, may lead to undesirable scenarios, negatively affecting operational safety. In aircraft engines there are a large number of fault root causes. Some of these faults in the high-pressure compressor (HPC) and high-pressure turbine (HPT) modules have symptoms that closely resemble highly deteriorated component states. Such faults may be accommodated by a structured manipulation of the engine control systems.
However, due to the highly nonlinear nature of the engine controller and the fact that it is implemented as a large collection of computer modules (typically over 100) that employ a variety of one- and two-input tables, switching variables, logical elements, limiters, and priority-select logic, to name a few, the control design space is high-dimensional, highly nonlinear, multimodal, and discontinuous. To find an optimal accommodation, it is very important, yet non-trivial, to define the performance metric in a flexible and non-analytical manner. This is necessary in order to properly account for such diverse requirements as maintaining stall margins above certain limits, minimizing both peak temperatures and the time spent above a certain temperature, and obtaining short rise times in response to changes in demand values. Furthermore, the changes must be accomplished over a wide range of flight conditions and disturbance inputs.
Only a very small portion of an overall engine control system is designed to operate in a linear fashion, and even then, the controller gains are often scheduled as functions of the operating conditions (altitude, Mach number, and ambient temperature deviation from standard day, for example). Although much is known about the behavior and design of linear control systems, this information is not relevant to the problems under consideration here. Rather, one must be prepared to work in the nonlinear domain, where theories and analytical results are much more scarce than for the linear domain. Also, the literature on nonlinear control systems, of necessity, tends to deal with specific situations, such as the area of integrator-windup protection (IWP).
It is not to be expected that conventional optimization methods and those that depend on gradient evaluations should work, and in view of the existing art, it would be beneficial to provide an application of evolutionary algorithms to aircraft engine control systems design, where the controls design and optimization is performed using a full-order engine model and full control systems structures that do not oversimplify the inherent complexities in these highly complex nonlinear dynamic systems. Accordingly, there is a need in the art for a non-conventional optimization method to provide real-time adjustments to the controller to recover from some or all of the engine faults.